Existing approaches for deterministic execution run all code sections in a fully deterministic manner, resulting in high performance costs and a loss of scalability. In this thesis we develop a programming model for a scalable deterministic execution of distributed applications, which introduces less performance costs than fully deterministic systems.
We introduce the concept of Application-level Determinism, which, in contrast to full determinism, limits the deterministic execution to code sections that potentially influence the deterministic result of the application when executed concurrently. Based on this concept, the Spawn & Merge programming model automates the decision whether the execution of two code segments must be kept in order to maintain a deterministic result. The evaluation of a prototype of Spawn & Merge for distributed systems shows that applications with a high share of parallelizable code can scale efficiently (achieve up to 100% of maximum speedup possible) and guarantee the deterministic and reproducible execution of the application logic.
The performance gain competes with the costs for the determinism-enforcing mechanisms used by Spawn & Merge: Operational Transformation (OT) and waiting conditions introduced. The majority of potential waiting conditions is automatically dealt with by internal dynamic scheduling of the parallel parts of the application. The remaining waiting conditions are further reduced by introducing a modified OT system that allows for an efficient deterministic merge in any given order. The costs for OT depend on the application and can take up most of the execution time (up to a worst case of 97,5% in the performed measurements) when many modifications of shared data structures are performed and when there is a high amount of synchronization between the parts of the application that are executed in parallel. This is due to the computational complexity of O(n^2) for the OT systems used. However, these costs for OT are constant for an application for a given input. Thus, the share of OT on the overall application runtime reduces with rising parallelism. Therefore, the feasibility of Spawn & Merge for an application depends on the parallelizable share of the application, the amount of performed modifications of shared data structures, and the amount of internal synchronizations.

Rights

Use and reproduction:

Export

DuEPublico
is the institutional repository of the University of Duisburg-Essen.
DuEPublico is driven by the university library and
based on the repository framework MyCoRe and additional Open Source components.
Find out more...